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With a large number of new energy vehicles being put into use, it is the general trend for traditional fuel vehicles to withdraw from the market in an orderly manner. Determining the optimal ratio between them in this process is of great significance to the low-carbon sustainable development of cities. Therefore, considering the constraints of urban automobile development planning and air pollution prevention and control policies, a multi-objective model to minimize pollutants and costs is constructed in this paper. Through model calculation and sensitivity analysis of dynamic impact relationship of different types of vehicles, it is determined that when new energy vehicles account for around 36% in Beijing, 57% in Shanghai and 46% in Guangzhou, the pollutant emissions can be minimized without causing a significant increase in social costs. Additionally, compared with 2030, Beijing, Shanghai and Guangzhou can achieve emission reductions of 320,000 tons, 200,000 tons and 250,000 tons, respectively, in 2050 if they implement the policy of banning the sale and delisting of fuel vehicles, which could provide suggestions for the guidance of the low-carbon development plan of the automobile industry. [ABSTRACT FROM AUTHOR]

The PM2.5 index is an important basis for measuring the degree of air pollution. The accurate prediction of PM2.5 concentration has an important guiding role in air pollution prevention and control. The Pearson Correlation Coefficient (PCC) is a common index used to mine the correlation between meteorological factors and other air pollutants. However, this index cannot be used to mine non-linear correlations, nor can it quantitatively analyze the weight of each related attribute. In order to accurately explore the correlation between meteorological factors and other air pollutants and to achieve an accurate prediction of PM2.5 concentration, this paper proposes a short- and long-time memory (LSTM) network prediction model based on Copula entropy (CE) and the adaptive genetic algorithm (AGA). By calculating CE, the correlation between multiple meteorological factors and various atmospheric pollutants and PM2.5 was analyzed. The correlation of influencing factors was sorted according to the size of the correlation coefficients. The contribution rate of meteorological factors and atmospheric pollutants to PM2.5 concentration was determined, used as the weight of each influencing factor and predicted as the input data of the prediction model. In this paper, a long- and short-term memory network (LSTM) suitable for time series data was selected as the prediction model, while the selection of model parameters was taken into account, and the relevant parameters were sought by an adaptive genetic algorithm (AGA). The air pollutant data and meteorological data of Beijing from 1 January 2016 to 31 December 2016 were selected, and MAE and RMSE were used as evaluation indexes. By comparing the experimental results of the CE-AGA-LSTM with those of other eight prediction models (LR, SVM, RF, ARMA, ST-LSTM, LSTM, CE-LSTM and CE-RNN), we found that among the models, the CE-AGA-LSTM model provided the lowest MAE and RMSE values, i.e., 14.5 and 21.88, respectively. At the same time, the loss rate and accuracy of the CE-AGA-LSTM model were evaluated, and the experimental results verified the validity of the model. [ABSTRACT FROM AUTHOR]

Pollution havens create environmental inequality issues. China's recent policy of directing high-pollution firms to migrate out of its capital, Beijing, offers a case of a pollution haven that was mandated, rather than resulting from firms' responses to environmental regulation. More importantly, it leads to a question that has been less discussed in previous literature: does a pollution haven strike back? After the highly polluting enterprises moved out of Beijing to neighboring Hebei province, Hebei has been blamed for the continuing poor air quality in Beijing, based on a perception that the pollutants emitted in Hebei are being blown back to Beijing. This paper investigates the existence of a pollution haven in Hebei and quantifies the contribution of Hebei's emissions to Beijing's air quality. We find that the proportion of output values and the relative concentration of high-pollution industries in Hebei increased when the large-scale out-migration began, while the indicators in Beijing decreased. We also find higher emissions of enterprises in Hebei than their counterparts in Beijing. Together, these findings indicate the existence of a "manmade" pollution haven. Further, based on high-frequency spatial data, we combine an Autoregressive Distributed Lag model and a Spatial Autoregressive Model and decompose the factors that affect Beijing's air quality into local and regional transport of air-borne pollutants. We find a significant effect of the neighboring cities' air pollution on Beijing's air quality. This indicates that the pollution haven indeed struck back. These findings imply the importance of regional policies to control air pollution. [ABSTRACT FROM AUTHOR]

The effectiveness of national policies for air pollution control has been demonstrated, but the relative effectiveness of short-term emission reduction measures in comparison with national policies has not. Here we show that short-term abatement measures during important international events substantially reduced PM2.5 concentrations, but air quality rebounded to pre-event levels after the measures ceased. Long-term adherence to strict emission reduction policies led to successful decreases of 54% in PM2.5 concentrations in Beijing, and 23% in atmospheric nitrogen deposition in China from 2012 to 2020. Incentivized by "blue skies" type campaigns, economic development and reactive nitrogen pollution are quickly decoupled, showing that a combination of inspiring but aggressive short-term measures and effective but durable long-term policies delivers sustainable air quality improvement. However, increased ammonia concentrations, transboundary pollutant flows, and the complexity to achieving reduction targets under climate change scenarios, underscore the need for the synergistic control of multiple pollutants and inter-regional action. In response to the rebound of air pollution during large events in China, the authors propose that a combination of ambitious short-term measures and enduring long-term pollution control policies is a sustainable solution for improving air quality. [ABSTRACT FROM AUTHOR]

Currently, air pollution is primarily characterized by PM 2.5 and O 3. Therefore, the co-control of PM 2.5 and O 3 has become an important task of atmosphere pollution prevention and control in China. However, few studies have been conducted on the emissions from vapor recovery and processes, which is an important source of VOCs. This paper analyzed the VOC emissions of three vapor process technologies in service stations and first proposed key pollutants for priority control based on the coordinated reactivity of O 3 and SOA. The concentration of VOCs emitted from the vapor processor was 3.14–9.95 g m−3, compared to 631.2–717.8 g m−3 for uncontrolled vapor. Alkanes, alkenes, and halocarbons accounted for a high proportion of the vapor both before and after control. Among the emissions, i -pentane, n -butane, and i -butane were the most abundant species. Then, the species of OFP and SOAP were calculated through the maximum incremental reactivity (MIR) and fractional aerosol coefficient (FAC). The average source reactivity (SR) value of the VOC emissions from three service stations was 1.9 g g−1, while the OFP ranged from 8.2 to 13.9 g m−3 and SOAP ranged from 0.18 to 0.36 g m−3. By considering the coordinated chemical reactivity of O 3 and SOA, a comprehensive control index (CCI) was proposed for the control of key pollutant species that have multiplier effects on environment. For adsorption, trans -2-butene and p -xylene were the key co-control pollutants, while toluene and trans -2-butene were the most important for membrane and condensation + membrane control. A 50% emission reduction of the top two key species that emission account for 4.3% averagely will reduce O 3 by 18.4% and SOA by 17.9%. [Display omitted] • The organized emissions of VOCs from three vapor processors were studied in service stations. • The species composition of VOCs before and after control were analyzed. • The OFP and SOAP were calculated to evaluate the secondary pollution. • The co-control of key pollutants based on SOA and O 3 has great environmental benefits. [ABSTRACT FROM AUTHOR]

Reliable observations of aerosol optical properties are crucial for quantifying the radiative forcing of climate. The simultaneous measurements of aerosol optical properties at three wavelengths for PM 1 and PM 10 were conducted in urban Beijing from March 2018 to February 2022. The aerosol absorption coefficient (σab) at 550 nm of PM 10 and PM 1 decreased by 55.0 % and 53.5 % from 2018 to 2021. The significant reduction in σab may be related to reduced primary emissions caused by effective air pollution control measures. PM 2.5 mass concentration decreased by 34.4 % from 2018 to 2021. Single scattering albedo (SSA) increased from 0.89±0.04 for PM 10 (0.87±0.05 for PM 1) in 2018 to 0.93±0.03 for PM 10 (0.91±0.04 for PM 1) in 2021. Increasing SSA and decreasing PM 2.5 mass concentration suggest that the fraction of absorbing aerosols decreased with improved air quality due to pollution control measures being taken. The annual average submicron absorption ratio (Rab) increased from 86.1 % in 2018 to 89.2 % in 2021, suggesting that fine particles are the main contributors to total PM 10 absorption and that the contribution of fine particles to absorption became more important. The absorption Ångström exponent (AAE) in winter decreased from 2018 to 2021, implying a decreasing contribution from brown carbon to light absorption, which may relate to the reduced emissions of biomass burning and coal combustion. During the study period, aerosol radiative forcing efficiency became more negative, mainly influenced by increasing SSA and was -27.0 and -26.2 W m -2 per aerosol optical depth (AOD) for PM 10 and PM 1 in 2021. Higher σab and PM 2.5 mass concentrations were primarily distributed in clusters 4 and 5, transported from the south and the west of Beijing each year. σab and PM 2.5 corresponding to clusters 4 and 5 decreased evidently from 2018 to 2021, which may result from the control of source emissions in surrounding regions of Beijing. The 4-year data presented in this study provide critical optical parameters for radiative forcing assessment within two size ranges and are helpful for evaluating the effectiveness of clean air action. [ABSTRACT FROM AUTHOR]

With a decrease in fine particulate matter (PM 2.5) due to the implementation of air pollution prevention-control measures, ozone (O 3) has risen in China especially in urban areas recently. It becomes more and more important to control air combined pollution with high concentration of PM 2.5 and O 3. We analyzed the characteristics of air combined pollution in Beijing from 2014 to 2019 in this paper. Results indicated that the trough O 3 showed an upward trend of 4.5 μg m−3 yr−1, while the peak decreased by −1.1 μg m−3 yr−1. There were three typical atmospheric chemical stages in the interaction between O 3 and PM 2.5 in summer through observations. The first was an intense photochemical stage with the synchronous and rapid growth of O 3 and PM 2.5. The O 3 concentration varied from 68 μg m−3 to 206 μg m−3 when PM 2.5 ≤ 35 μg m−3. While secondary inorganic ions (SNA) ranged from 2 to 21 μg m−3 especially SO 4 2− (0.8–12 μg m−3). The second was an aerosol chemical generation stage with the rapid increase of PM 2.5 and SNA under high O 3 concentration. O 3 was maintained at a high concentration between 198 μg m−3 and 241 μg m−3 when PM 2.5 was within the range of 35–125 μg m−3. SNA increased from 12 μg m−3 to 96 μg m−3. The third was a high PM 2.5 pollution stage suppressing the generation of O 3 when PM 2.5 ≥ 125 μg m−3. O 3 began to decline with the growth of PM 2.5 and decreased from 224 μg m−3 to 130 μg m−3. Ultraviolet radiation (UV) decreased from 13 MJ m−3 in the first to 8 MJ m−3 in this stage. [Display omitted] • The O 3 trough increased by 4.5 μg/m3 and the peak decreased by −1.1 μg/m3 per year in Beijing. • There were three typical processes in the interaction between O 3 and PM 2.5 in summer day. • The photochemical process was intense in dry-sunny days with the synchronous growth of O 3 and PM 2.5. • Aerosol chemical process intensified with a rapid growth of PM 2.5 and SNA in high O 3. • O 3 began to decline with the growth of PM 2.5 when PM 2.5 attenuated UV in a high level. [ABSTRACT FROM AUTHOR]

(1) Background: To better carry out air pollution control and to assist in accurate investigations of air pollution, in this study, we fully explore the spatial distribution characteristics of air pollution complaint results and provide guidance for air pollution control by combining regional air monitoring data. (2) Methods: By selecting the air pollution complaint information in Beijing from 2019 to 2020, in this study, we extract the names and addresses of complaint points, as well as the complaint times and types by adopting the BERT (bidirectional encoder representations from transformers) + CRF (conditional random field) model deep learning method. Moreover, through further filtering and processing of the complaint points' address information, we achieve address matching and spatial positioning of the complaint points, and realize the regional spatial representation of air pollution complaints in Beijing in the form of a heat map. (3) Results: The experimental results are compared and analyzed with the ranking data of total suspended particulate (TSP) concentration of townships (streets) in Beijing during the same period, indicating that the key areas of air pollution complaints have a high correlation with the key polluted township (street) areas. The distribution of complaints and the types of complaints in each township (street) differ according to the population density in each township (street), the level of education, and economic activity. (4) Conclusions: The results of this study show that the public, as the intuitive perceiver of air pollution, is sensitive to the air pollution situation at a smaller spatial scale; furthermore, complaints can provide guidance and reference for the direction of air pollution control and law enforcement investigations when coupled with geographical features and economic status. [ABSTRACT FROM AUTHOR]

Strict air pollution control strategies have been implemented in recent decades in the North China Plain (NCP), previously one of the most polluted regions in the world, and have resulted in considerable changes in emissions of air pollutants. However, little is so far known about the long-term trends of the regional background level of NOx and SO2 , along with the increase and decrease processes of regional emissions. In this study, the seasonal and diurnal variations of NOx and SO2 as well as their long-term trends at a regional background station in the NCP were characterized from 2004 to 2016. On average, SO2 and NOx mixing ratios were 5.7 ± 8.4 and 14.2 ± 12.4 ppb , respectively. The seasonal variations in SO2 and NOx mixing ratios showed a similar pattern, with a peak in winter and a valley in summer. However, the diurnal variations in SO2 and NOx mixing ratios greatly differed for all seasons, indicating different sources for SO2 and NOx and meteorological effects on their concentrations. Overall, the annual mean SO2 exhibited a significant decreasing trend of - 6.1 %yr-1 (R = - 0.84, P < 0.01) from 2004 to 2016, which is very close to - 6.3 %yr-1 of the annual SO2 emission in Beijing, and a greater decreasing trend of - 7.4 %yr-1 (R = - 0.95, P < 0.01) from 2008 to 2016. The annual mean of NOx showed a fluctuating rise of + 3.4 %yr-1 (R = 0.38, P = 0.40) from 2005 to 2010, reaching the peak value (16.9 ppb) in 2010, and then exhibited an extremely significant fluctuating downward trend of - 4.5 %yr-1 (R = 0.95, P < 0.01) from 2010 to 2016. After 2010, the annual mean NOx mixing ratios correlated significantly (R = 0.94, P < 0.01) with the annual NOx emission in North China. The decreasing rate (- 4.8 %yr-1 , R = - 0.92, P < 0.01) of the annual mean NOx mixing ratios from 2011 to 2016 at the Shangdianzi (SDZ) regional atmospheric background station is lower than the one (- 8.8 %yr-1 , R = - 0.94, P < 0.01) for the annual NOx emission in the NCP and in Beijing (- 9.0 %yr-1 , R = - 0.96, P < 0.01). This indicated that surface NOx mixing ratios at SDZ had a weaker influence than SO2 on the emission reduction in Beijing and its surrounding areas in the NCP. The increase in the number of motor vehicles led to an increase in traffic emissions for NOx. This study supported conclusions from previous studies that the measures taken for controlling NOx and SO2 in the NCP in the past decades were generally successful. However, NOx emission control should be strengthened in the future. [ABSTRACT FROM AUTHOR]